Mathematical Problems of Analysis and Synthesis of Complex Systems
Course: Applied Mathematics
Structural unit: Faculty of Computer Science and Cybernetics
            Title
        
        
            Mathematical Problems of Analysis and Synthesis of Complex Systems
        
    
            Code
        
        
            ВК.2.03
        
    
            Module type 
        
        
            Вибіркова дисципліна для ОП
        
    
            Educational cycle
        
        
            First
        
    
            Year of study when the component is delivered
        
        
            2024/2025
        
    
            Semester/trimester when the component is delivered
        
        
            6 Semester
        
    
            Number of ECTS credits allocated
        
        
            4
        
    
            Learning outcomes
        
        
            LO 2. Be able to use basic principles and methods of mathematical, complex and functional analysis, linear algebra and number theory, analytical geometry, and differential equations, including partial differential equations, probability theory, mathematical statistics and random processes, numerical methods.
LO 5. Be able to develop and use in practice algorithms related to the approximation of functional dependencies, numerical differentiation and integration, solving systems of algebraic, differential and integral equations, solving boundary value problems, finding optimal solutions.
PLO 22.2. Have knowledge of the mathematical modeling and optimal management fundamentals, to the extent necessary for the development of applied disciplines and use the relevant knowledge in the chosen profession.
        
    
            Form of study
        
        
            Full-time form
        
    
            Prerequisites and co-requisites
        
        
            To successfully study the discipline "Problems of analysis and synthesis of Systems" the student must meet the following requirements:
Know:
1. theoretical bases and methods of construction, verification, and research of qualitative characteristics of mathematical models.
2. principles of application of methods of simulation modeling and self-organization of mathematical models.
Be able to:
1. investigate the quantitative and qualitative characteristics of mathematical models.
2. formulate mathematical optimization problems for such models.
Have the skills:
1. basic skills in using MATLAB and STATISTICA application packages.
2. in English at a level not lower than Intermediate.
        
    
            Course content
        
        
            The aim of the course is to master methods for constructing, verifying, and studying the qualitative characteristics of mathematical models, and to apply them to the formulation and solution of modeling and optimization problems of complex systems.
        
    
            Recommended or required reading and other learning resources/tools
        
        
            1. Bielov Yu.A., Khusainov T.D., Shatyrko A.V. Strukturne modeliuvannia v dynamichnykh systemakh. Visnyk Kyiv Un-tu. Kibernetyka. Vyp. 7, Kyiv, 2007. pp. 4-7.
2. William F. Sharpe, Gordon J. Alexander, Jeffery V. Bailey, Prentice Hall, 2018. – Investment analysis. – 962 p.
3. Kyrylych V.M. Rekursyvni metody dynamichnoi ekonomiky. /V.M. Kyrylych, V.A. Kozytskyi. – Lviv: VTs LNU imeni Ivana Franka, 2012. – 84 p.
4. Kulian V.R. Metody optymalnoho keruvannia v zadachakh dyversyfikatsii portfelia invectytsii. Visnyk KNU imeni Tarasa Shevchenka. S.: kibernetyka. – vyp. 1(15), 2015. – pp. 18-32.
5. Kulian V.R. Matematychne modeliuvannia ta optymizatsiia finansovo-ekonomichnykh protsesiv. Kurs lektsii. [Elektronnyi resurs]. Rezhym dostupu www.195.68.210.50/moodle/. – 2014. – 84 p.
6. Kulian V.R., Yunkova O.O. Matematychne modeliuvannia ta optymizatsiia finansovo-ekonomichnykh protsesiv. Navchalnyi posibnyk. K.: «Kyivskyi universytet», 2016. – 112 p.
        
    
            Planned learning activities and teaching methods
        
        
            Lectures, independent work, elaboration of recommended literature, homework.
        
    
            Assessment methods and criteria
        
        
            Semester Assessment:
The maximum number of points a student can earn is 100:
1. Test No. 1: 50/30 points.
2. Test No. 2: 50/30 points.
        
    
            Language of instruction
        
        
            Ukrainian
        
    Lecturers
This discipline is taught by the following teachers
                    Victor
                    R.
                    Kulian
                
                
                    Complex systems modelling 
Faculty of Computer Science and Cybernetics
            Faculty of Computer Science and Cybernetics
                    Andriy
                    V.
                    Shatyrko
                
                
                    Complex systems modelling 
Faculty of Computer Science and Cybernetics
            Faculty of Computer Science and Cybernetics
Departments
The following departments are involved in teaching the above discipline
                        Complex systems modelling
                    
                    
                        Faculty of Computer Science and Cybernetics
                    
                
                        Complex systems modelling
                    
                    
                        Faculty of Computer Science and Cybernetics